alt Hacker NewsThe curiosity is inefficient though. So many times I have to stop the agent and tell it to just fucking write the code and try compiling it. Otherwise it will fill its entire context tracing through the program logic to derive from the code itself whether the thing it is about to do would work. It completely fails to notice it can just… try.
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I think I use it differently. I still mainly stick to web UI.
I write a good prompt, paste the code then copy the output code and place it into my project.
So in the end I hand assemble and I only give it what it needs to know so no extra context wasted.
The human in the loop is of course the secret sauce but this way I am highly efficient, no vibecode and I work really fast too. Everything is audited.
It's tuned for the kinds of tasks where "just try" doesn't get good results.
A major complaint with AI code was that AIs struggle with complex codebases, don't respect existing conventions, reinvent functionality multiple times over, etc. So, newer high end AIs are tuned with the "explore/exploit" dial turned towards "explore".
You could probably get it to do things "quick and dirty" with prompting, but that, of course, requires prompting for it.
Everything about LLMs is inefficient. They have their benefits but watching them reason over things that are painfully obvious, that they've literally investigated before (before a memory compaction), never take a step back aand be like 'this is going too slow let me look for a better way', etc. is painful.